Leveraging Renewable Energy in Edge Clouds for Data Stream Analysis in IoT
Leveraging Renewable Energy in Edge Clouds for Data Stream Analysis in IoT
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DOI：
10.1109/ccgrid.2017.92
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发表时间：
2017-05
期刊：
影响因子：
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通讯作者：
Yunbo Li;Anne-Cécile Orgerie;I. Rodero;M. Parashar;Jean-Marc Menaud
中科院分区：
文献类型：
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作者：
Yunbo Li;Anne-Cécile Orgerie;I. Rodero;M. Parashar;Jean-Marc Menaud
物联网（IoT）的出现正在参与数据和能源需求的应用程序的增加。由于连接的设备还没有提供足够的能力来维持这些应用程序，用户将计算卸载到云端。为了避免网络瓶颈并降低与数据移动相关的成本，边缘云解决方案已开始部署，从而提高服务质量。在本文中，我们提倡利用不同边缘云节点中的现场可再生能源生产来实现绿色物联网系统，同时与核心云解决方案相比，提供更高的QoS。我们提出了一个分析模型来决定是否将计算从对象卸载到边缘或核心云，这取决于可再生能源的可用性和所需的应用QoS。该模型在我们的应用程序用例中进行了验证，该用例处理来自车载摄像头的视频流分析。
The emergence of Internet of Things (IoT) is participating to the increase of data-and energy-hungry applications. As connected devices do not yet offer enough capabilities for sustaining these applications, users perform computation offloading to the cloud. To avoid network bottlenecks and reduce the costs associated to data movement, edge cloud solutions have started being deployed, thus improving the Quality of Service. In this paper, we advocate for leveraging on-site renewable energy production in the different edge cloud nodes to green IoT systems while offering improved QoS compared to core cloud solutions. We propose an analytic model to decide whether to offload computation from the objects to the edge or to the core Cloud, depending on the renewable energy availability and the desired application QoS. This model is validated on our application use-case that deals with video stream analysis from vehicle cameras.